Classifications

• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06V—IMAGE OR VIDEO RECOGNITION OR UNDERSTANDING
  • G06V10/00—Arrangements for image or video recognition or understanding
  • G06V10/20—Image preprocessing
• • H—ELECTRICITY
  • H03—ELECTRONIC CIRCUITRY
  • H03M—CODING; DECODING; CODE CONVERSION IN GENERAL
  • H03M7/00—Conversion of a code where information is represented by a given sequence or number of digits to a code where the same, similar or subset of information is represented by a different sequence or number of digits
  • H03M7/30—Compression; Expansion; Suppression of unnecessary data, e.g. redundancy reduction
• • G—PHYSICS
  • G06—COMPUTING; CALCULATING OR COUNTING
  • G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
  • G06T9/00—Image coding

Definitions

• the present invention relates generally to the compression and retrieval of data representing a font or other set of symbols; and, more particularly, to a method and apparatus for storing a large font, such as a Chinese or Japanese character set, in a compressed form while retaining access to individual symbols of the font.
• the Chinese Unicode standard character set contains about 21,000 different Chinese symbols.
• each symbol is the size of at least some hundreds of pixels; and, as a result, to store a complete Chinese font requires a large amount of memory. Being able to store the glyphs in a more compact format than pure bitmaps will substantially reduce memory requirements.
• a font is usually stored as a series of points that are joined by curves. This brings the additional advantage of making font scaling possible, although for fonts stored in this way, some processing is needed to render the image itself. For lower resolution displays, font scaling is not of interest, and it would be more efficient to store the font as a bitmap.
• a two-part code can also be used to compress and retrieve a font.
• the first part of such a code describes the statistical properties, or a model, of the data; and the second part encodes the data by a code derived from the model.
• Exemplary of font compression and retrieval methods known in the prior art include those described in U.S. Patent Nos. 5,488,365; 5,058,187; 5,587,725; 5;473;704; and 5,020,121 ; and PCT Publication No. WO 98/16902.
• none of these prior art methods describes a font compression and retrieval technique that provides complete random access of individual symbols of the font, which is important to permit high-speed access of the symbols by modern high-speed equipment.
• the present invention is directed to a method and apparatus for the compression and retrieval of data representing a set of symbols; and, particularly, to a method and apparatus for compressing a font which comprises a large number of glyphs, such as a Chinese or a Japanese character set, in such a manner that each individual glyph of the character set can be separately accessed and decompressed.
• a method for compressing data representing a set of symbols includes encoding each symbol of the set of symbols in the form of a two-part code wherein a first part of the two-part code is common for all encoded symbols of the set and a second part of the two-part code comprises encoded data representing a symbol of the set, wherein each encoded symbol of the set can be separately accessed and decompressed.
• the present invention provides a data compression method that is based on the use of a two-part code, however, the first part of the code is common for all symbols of the set of symbols, and this allows each encoded symbol to be separately accessed and decompressed.
• the present invention accordingly, provides the property of random access to the individual symbols of the set which, as indicated above, is a particularly important capability in modern high-speed equipment.
• the set of symbols comprises a font of individual symbols or glyphs
• the data representing the glyphs includes a bitmap for each glyph.
• a statistical model of the set of glyphs is created (the first part of the two-part code or the "model"), and each glyph is then separately compressed with a code derived from the model (the second part of the two-part code or the "codeword").
• the compressed glyphs are partitioned by codeword length, and one indexing table, sorted by an identifier for each glyph, is created for each partition.
• An encoded font will thus comprise a statistical model, a set of codewords, a set of indexing tables, a table of lengths for the indexing tables and, perhaps, auxiliary tables used for decoding.
• the indexing tables are first searched for a matching entry. From the table lengths and the position in the table, the position or location of the particular glyph in the code set can be computed, and this permits the desired codeword for that glyph to then be extracted and decoded. Because, in the present invention, a two-part code is used where the first part of the code is common for all the encoded glyphs; indexing is greatly simplified inasmuch as for each glyph it is only necessary to locate the codeword for that particular glyph.
• font compression is achieved utilizing an arithmetic encoder with a fixed probability table. This procedure provides near optimal compression of the glyphs, given the probability table, without the need of additional tables.
• font compression is by means of a predictive encoding scheme with a fixed prediction table followed by a fixed Huffman coding. This procedure makes it possible to have a very fast decompression while retaining reasonable compression speeds. This embodiment is also particularly suitable for hardware implementation.
• FIGURE 1 schematically illustrates an encoder for a font compression scheme according to a first presently preferred embodiment of the invention
• FIGURE 2 schematically illustrates one example of a conditioning context of a pixel to assist in explaining the operation of the encoder of FIGURE 1
• FIGURE 3 schematically illustrates a decoder for retrieving data encoded by the encoder of FIGURE 1;
• FIGURE 4 schematically illustrates an encoder for a font compression scheme according to a second presently preferred embodiment of the invention
• FIGURES 5 and 6 are flow charts illustrating the basic steps of the encoding and decoding procedures, respectively, for a font compression and retrieval method according to the present invention.
• FIGURE 1 is a block diagram schematically illustrating the encoder structure of a compression scheme according to a first embodiment of the present invention for compressing data representing a set of symbols such as a font of Chinese or Japanese symbols or glyphs.
• the sequence of bits output from the serialize module 14 is directed to an arithmetic encoder module 16 which may be a standard binary arithmetic encoding unit (see, for example, C.B. Jones, "An Efficient Coding System for Long Source Sequences", IEEE Transactions on Information Theory, vol. 27, no. 3, pp. 280-291 , May, 1981).
• arithmetic precision of the encoder should be matched with the precision of the probability table that will be discussed hereinafter.
• the bits are encoded sequentially as the bitmap is scanned.
• the model that provides the coding probabilities for the arithmetic coding is illustrated by dashed block 18 and is designated in FIGURE 1 as a source model.
• the source model is context based, i.e., the probability distribution of each pixel of the bitmap is determined by a conditioning context of surrounding pixel values.
• the model includes a context forming unit or module 22 which selects bits from previously encoded ones in the same bitmap to determine the context, which is represented as an integer.
• FIGURE 2 schematically illustrates one example of the correspondence between context pixels and bit positions.
• the conditioning context of any pixel must contain only pixels that appear earlier in the scan order. Its shape may vary depending on the pixel. Any context pixel outside the bitmap is set to zero.
• the source model 18 also includes a probability table 24 which has one entry per possible context, containing the pixel probability conditioned on that context, stored with fixed precision.
• the probability table 24 is constructed by counting the occurrences of ones in each context, and normalizing by the number of occurrences of the context.
• byte alignment module 26 If only certain codeword lengths are allowed, for instance integer bytes, zeros are appended to the end of the output of the arithmetic encoder by byte alignment module 26.
• the output of the byte alignment module is the codeword representing a symbol or glyph of the font.
• Each glyph of the font is encoded utilizing the encoder of FIGURE 1 until the entire font has been encoded and stored in memory.
• the scan order and the context forming function are chosen. Different sizes of contexts, scan orders, context forming functions, and precisions of the probability table can be tried in order to find the one yielding the best compression.
• the quantity that is minimized here to yield the best compression is the size of the codeword set plus the size of the probability table.
• the codewords produced by the above procedure are sorted first by length and then by identifier, which is given for each glyph of the font, and an index table for each length is constructed as a list of identifiers sorted in ascending order. For each index table is stored in a length table the codeword length it corresponds to, and the table length.
• the codewords are stored together with the index table and the length table. It should be noted that the information about the location and length of each codeword in memory is present only in the index and length tables, i.e., the codewords are stored sorted by length and identifier but without any separators.
• the index tables are first searched one by one, using a binary search. If the identifier is found, the address of the corresponding codeword is found by summing the product of the codeword length and the number of codewords of that length over all codeword lengths smaller than the one of the searched table (counting of the codewords should begin at zero), and adding the codeword length of the searched table times the position of the identifier in the table.
• Other search orders of the tables are also possible. For instance, one could search the tables in order of descending size, if desired; and it is not intended to limit the invention to any particular search order. It should also be understood that other searching methods can be used as well without departing from the scope of the present invention, and it is also not intended to limit the invention to any particular searching method.
• FIGURE 3 is a block diagram schematically illustrating the structure of an encoder
• FIGURE 4 the probability table of the source model 18 of the encoder 10 of FIGURE 1 is replaced by a prediction table 42 in a source model 48 in which each entry is one bit, indicating the most probable bit value in each context.
• the predicted value for each bit is exclusive- ORed with the actual bit by unit 44, producing a bit stream that is encoded by a Huffman code in Huffman encoder module 46 (see D.A. Huffman, "A Method for the Construction of Minimum-Redundancy Codes", Proc. IRE, vol. 40, pp 1098-1101, 1952.)
• FIGURES 5 and 6 are flowcharts which generally illustrate the steps of the encoding and decoding procedures, respectively, of the compression and retrieval methods of the present invention.
• two-dimensional bitmaps of the individual symbols or glyphs of the font are serialized at step 61 using the serializer 14 shown in FIGURES 1 or 4.
• a source or statistical model of the serialized data is created at step 62 using the context forming module 22 and either the probability table 24 of FIGURE 1 or the prediction table of FIGURE 4.
• the sequence of bits output from the serializer is then encoded in step 63 where each symbol or glyph of the font is independently encoded with a code derived from the statistical model by either the arithmetic encoder 16 of FIGURE 1 or the Huffman encoder 46 of FIGURE 4 to provide the encoded codeword set representing the font.
• the encoded font is then stored in memory at step 64 for later retrieval, for example. As indicated above, the codewords are stored together with the index table and the length table.
• the index tables are first searched in step 71 until the identifier for the encoded symbol is found.
• the address of the stored encoded symbol is then found using the identifier, step 72; and, finally, the codeword is retrieved and decoded, step 83, using the decoder of, for example, FIGURE 3, to provide the decompressed bitmap of the selected symbol or glyph.
• An important aspect of the present invention is that a two-part code is used wherein the first part of the code, i.e., the model, is common for all the encoded glyphs; and the second part of the code, i.e., the codeword, comprises the encoded data representing a glyph.
• the first part of the code i.e., the model
• the second part of the code i.e., the codeword
• an arithmetic coder with a fixed probability table is used, which ensures near optimal compression of the glyphs, given the probability table, without the need for additional tables, as distinguished from Lempel-Ziv and Huffman coding schemes which perform poorly on short data blocks and require extensive code tables, respectively.
• each table is reduced to a list of identifiers.
• the total size of the addressing tables are only marginally larger than the space originally occupied by the identifiers; and, thus, we have gained the property of random access to the glyphs with only a slight increase in index table size.

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• 2001
  • 2001-02-27 US US09/794,706 patent/US20020118885A1/en not_active Abandoned
• 2002
  • 2002-02-15 WO PCT/EP2002/001601 patent/WO2002069269A2/en active IP Right Grant
  • 2002-02-15 EP EP02744894A patent/EP1364343B1/de not_active Expired - Lifetime
  • 2002-02-15 KR KR1020037010349A patent/KR100906041B1/ko active IP Right Grant
  • 2002-02-15 AT AT02744894T patent/ATE333683T1/de not_active IP Right Cessation
  • 2002-02-15 DE DE60213205T patent/DE60213205T2/de not_active Expired - Lifetime
• 2004
  • 2004-08-06 US US10/913,639 patent/US7212679B2/en not_active Expired - Lifetime

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